Using AI to amplify our thinking, not replace it

When it comes to AI, there’s been a quiet, but seismic shift.

Can you feel it?

Not out in the noisy headlines. Or on your social feeds.

It’s happening on the ground – in studios, sprints and stand-ups.

The AI shift

AI is shifting beyond am experimental novelty and fast becoming a work staple.

As digital folks, we’ve felt this change as we’ve started integrating AI into our everyday workflows with AI agents and layers bursting onto our everyday platforms. Let’s be clear. Many – if not most – AI products are flawed.

But flawed does not mean useless, and as masters of our respective crafts, we know what good is. And what isn’t.

So we’re able to use AI thoughtfully and judiciously to be better at our work.

And better is something we take very seriously here at Jude.

Better work, better outcomes, better world.

Here’s how our team are using it.

Designers: Speed, spark and sanity checks

With a multidisciplinary team of designers, we all use AI slightly differently, but we can all agree on one thing.

AI is a process. Not just a product.

The refining. The back and forth. The trial and error. It’s not unlike the messy design process we all love.

This mindset anchors how we approach AI across the design process – bringing AI in when it makes sense and leaving it behind when it doesn’t.

Service Design

“I like using AI to support how we organise and review research notes,” says our Service Design Lead, Maddi Collings.

Tools like Figjam’s AI features can give us a head start with mapping early patterns or clustering data, helping with identifying themes and affinity mapping.

This frees our team up to focus on the real value of research activities – drawing meaning from what users are telling us!

“It means we end up with more meaningful, practical insights for our clients,” says Maddi. “So they know how to elevate their digital products and services.”

Experience design

“Design is such a collaborative exercise, so when I find myself without another human to bounce ideas off, I’ll use AI as a springboard to generate and filter through those early-stage ideas,” says Design Lead, Anna Morgan.

The team also use AI as a design sanity check.

It’s helped us check things like whether a colour palette is accessible or cohesive, or if our UI designs meet certain accessibility requirements.

Content design

“As a content designer, I often have to wade deep into complex topics I know nothing about – tax, superannuation, carbon emission modelling,’ says Content Lead, Vivien Luu.

“This is when tools like Perplexity AI have been helpful, allowing me to dive into a topic, and more importantly check the sources.”

This doesn’t replace the pair writing exercises our team run with subject matter experts. If anything, it supercharges them.

“It gets our knowledge base up to a level where we can ask more pointed, meaningful questions in the session,” says Vivien.

“And once we can understand something, we can write it better for users.”

And yes, our team absolutely use AI tools like ChatGPT and Claude Opus for writing. But only for early drafts.

While I love how AI spits words out like popcorn. There’s still this bland monotony to the way it writes. So, I’ll use it for drafting, structure and to generate ideas, but not for the actual writing (yet).

Delivery: From chaos to clarity

Our delivery team run some incredibly large-scale, complex projects where clarity is essential. This is where AI has been helpful.

“I’ve used AI to create aspects of project documentation,” says Sophie Wright, Delivery Lead and Jude Co-Founder.

“This has included writing user story requirements using clear and concise language that developers, designers and stakeholders alike can understand.”

“It can also be useful in sorting and prioritising tasks based on effort/impact analysis, rather than manually sticky-noting everything. As much as I love a good post-it note!”

Developers: Coding smarter, not harder

Our developers use AI to reduce the busywork and stay focused on what matters – building smart, reliable solutions. We lean on it for code scaffolding, writing unit tests, checking accessibility, generating documentation, and drafting release notes. It’s especially useful for improving consistency across large codebases and helping us deliver with confidence.

“It’s not replacing the work, it’s streamlining it,” says Tech Lead, Kate Hogden. “It means we can spend less time on repetition and more time on the thinking.”

The decisions, trade-offs and architecture still come down to us. AI just helps us get there faster — and with fewer distractions.

Better together

When used thoughtfully, AI can be a brilliant collaborator and force multiplier.

It’ll open up new experiences to design for, new technologies to deliver and plenty of greenfield opportunities to explore.

At Jude, we like to make it better, together.

This couldn’t be truer with our AI collaborators.